INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance

AbstractA new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Here, we launch INSaFLU (“INSide the FLU”), which, to the best of our knowledge, is the first influenza-specific bioinformatics free web-based suite that deals with primary data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform advanced, multi-step software intensive analyses in a user-friendly manner without previous training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects’ management, being a transparent and highly flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus completely cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tune data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants, but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. In summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.INSaFLU can be accessed through https://insaflu.insa.pt (see homepage view in Figure 1).

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Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

Diagnostics ◽

10.3390/diagnostics11020201 ◽

2021 ◽

Vol 11 (2) ◽

pp. 201

Author(s):

Sang Mee Hwang ◽

Hee Won Cho ◽

Tae Yeul Kim ◽

Jeong Su Park ◽

Jongtak Jung ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Acinetobacter Baumannii ◽

Genome Sequencing ◽

Snp Analysis ◽

Whole Genome ◽

Phylogenetic Tree Analysis ◽

Web Based ◽

Hospital Outbreak ◽

Carbapenem Resistant ◽

Bioinformatics Tools

Carbapenem-resistant Acinetobacter baumannii (CRAB) outbreaks in hospital settings challenge the treatment of patients and infection control. Understanding the relatedness of clinical isolates is important in distinguishing outbreak isolates from sporadic cases. This study investigated 11 CRAB isolates from a hospital outbreak by whole-genome sequencing (WGS), utilizing various bioinformatics tools for outbreak analysis. The results of multilocus sequence typing (MLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic tree analysis by WGS through web-based tools were compared, and repetitive element polymerase chain reaction (rep-PCR) typing was performed. Through the WGS of 11 A. baumannii isolates, three clonal lineages were identified from the outbreak. The coexistence of blaOXA-23, blaOXA-66, blaADC-25, and armA with additional aminoglycoside-inactivating enzymes, predicted to confer multidrug resistance, was identified in all isolates. The MLST Oxford scheme identified three types (ST191, ST369, and ST451), and, through whole-genome MLST and whole-genome SNP analyses, different clones were found to exist within the MLST types. wgSNP showed the highest discriminatory power with the lowest similarities among the isolates. Using the various bioinformatics tools for WGS, CRAB outbreak analysis was applicable and identified three discrete clusters differentiating the separate epidemiologic relationships among the isolates.

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Whole genome sequencing suggests transmission of Corynebacterium diphtheriae-caused cutaneous diphtheria in two siblings, Germany, 2018

Eurosurveillance ◽

10.2807/1560-7917.es.2019.24.2.1800683 ◽

2019 ◽

Vol 24 (2) ◽

Cited By ~ 3

Author(s):

Anja Berger ◽

Alexandra Dangel ◽

Tilmann Schober ◽

Birgit Schmidbauer ◽

Regina Konrad ◽

...

Keyword(s):

Next Generation Sequencing ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Corynebacterium Diphtheriae ◽

Whole Genome ◽

Next Generation ◽

Insect Bites ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Generation Sequencing

In September 2018, a child who had returned from Somalia to Germany presented with cutaneous diphtheria by toxigenic Corynebacterium diphtheriae biovar mitis. The child’s sibling had superinfected insect bites harbouring also toxigenic C. diphtheriae. Next generation sequencing (NGS) revealed the same strain in both patients suggesting very recent human-to-human transmission. Epidemiological and NGS data suggest that the two cutaneous diphtheria cases constitute the first outbreak by toxigenic C. diphtheriae in Germany since the 1980s.

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Whole Genome Sequencing of A(H3N2) Influenza Viruses Reveals Variants Associated with Severity during the 2016–2017 Season

Viruses ◽

10.3390/v11020108 ◽

2019 ◽

Vol 11 (2) ◽

pp. 108 ◽

Cited By ~ 10

Author(s):

Bruno Simon ◽

Maxime Pichon ◽

Martine Valette ◽

Gwendolyne Burfin ◽

Mathilde Richard ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Influenza Viruses ◽

Influenza Surveillance ◽

Whole Genome ◽

University Hospitals ◽

Surveillance Network ◽

Genetic Traits ◽

H3n2 Influenza ◽

The Impact

Influenza viruses cause a remarkable disease burden and significant morbidity and mortality worldwide, and these impacts vary between seasons. To understand the mechanisms associated with these differences, a comprehensive approach is needed to characterize the impact of influenza genomic traits on the burden of disease. During 2016–2017, a year with severe A(H3N2), we sequenced 176 A(H3N2) influenza genomes using next generation sequencing (NGS) for routine surveillance of circulating influenza viruses collected via the French national influenza community-based surveillance network or from patients hospitalized in the intensive care units of the University Hospitals of Lyon, France. Taking into account confounding factors, sequencing and clinical data were used to identify genomic variants and quasispecies associated with influenza severity or vaccine failure. Several amino acid substitutions significantly associated with clinical traits were found, including NA V263I and NS1 K196E which were associated with severity and co-occurred only in viruses from the 3c.2a1 clade. Additionally, we observed that intra-host diversity as a whole and on a specific set of gene segments increased with severity. These results support the use of whole genome sequencing as a tool for the identification of genetic traits associated with severe influenza in the context of influenza surveillance.

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Whole genome sequencing of fecal samples as a tool for the diagnosis and genetic characterization of norovirus

Journal of Clinical Virology ◽

10.1016/j.jcv.2015.10.003 ◽

2015 ◽

Vol 72 ◽

pp. 122-125 ◽

Cited By ~ 13

Author(s):

Herjan H.J. Bavelaar ◽

Janette Rahamat-Langendoen ◽

Hubert G.M. Niesters ◽

Jan Zoll ◽

Willem J.G. Melchers

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genetic Characterization ◽

Whole Genome ◽

Fecal Samples

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Practices and views of neurologists regarding the use of whole-genome sequencing in clinical settings: a web-based survey

European Journal of Human Genetics ◽

10.1038/ejhg.2017.64 ◽

2017 ◽

Vol 25 (7) ◽

pp. 801-808 ◽

Cited By ~ 6

Author(s):

Iris Jaitovich Groisman ◽

Thierry Hurlimann ◽

Amir Shoham ◽

Béatrice Godard

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Clinical Settings ◽

Whole Genome ◽

Web Based

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Five-year Microevolution of a Multidrug-Resistant Mycobacterium Tuberculosis Strain within a Patient with Inadequate Compliance to Treatment.

10.21203/rs.3.rs-251738/v1 ◽

2021 ◽

Author(s):

Dario Fernández Do Porto ◽

Johana Monteserin ◽

Josefina Campos ◽

Ezequiel J Sosa ◽

Mario Matteo ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Genome Sequence ◽

Treatment Compliance ◽

Whole Genome Sequence ◽

Intermittent Therapy ◽

Whole Genome ◽

Short Term ◽

Depth Analysis

Abstract BackgroundWhole-genome sequencing has shown that the Mycobacterium tuberculosis infection process can be more heterogeneous than previously thought. Compartmentalized infections, exogenous reinfections, and microevolution are manifestations of this clonal complexity. The analysis of the mechanisms causing the microevolution —the genetic variability of M. tuberculosis at short time scales— of a parental strain into clonal variants with a patient is a relevant issue that has not been yet completely addressed. To our knowledge, a whole genome sequence microevolution analysis in a single patient with inadequate adherence to treatment has not been previously reported.Case Presentations In this work, we applied whole genome sequencing for a more in-depth analysis of the microevolution of a parental Mycobacterium tuberculosis strain into clonal variants within a patient with poor treatment compliance in Argentina. We analyzed the whole-genome sequence of 8 consecutive Mycobacterium. tuberculosis isolates obtained from a patient within 57-month of intermittent therapy. Nineteen mutations (9 short-term, 10 fixed variants) emerged, most of them associated with drug resistance. The first isolate was already resistant to isoniazid, rifampicin, and streptomycin, thereafter the strain developed resistance to fluoroquinolones and pyrazinamide. Surprisingly, isolates remained susceptible to the pro-drug ethionamide after acquiring a frameshift mutation in ethA, a gene required for its activation. We also found a novel variant, (T-54G), in the 5' untranslated region of whiB7 (T-54G), a region allegedly related to kanamycin resistance. Notably, discrepancies between canonical and phage-based susceptibility testing to kanamycin were previously found for the isolate harboring this mutation. In our patience, microevolution was mainly driven by drug selective pressure. Rare short-term mutations fixed together with resistance-conferring mutations during therapy.ConclusionsThis report highlights the relevance of whole-genome sequencing in the clinic for characterization of pre-XDR and MDR resistance profile, particularly in patients with incomplete and/or intermittent treatment.

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Overlapping of independent SARS-CoV-2 nosocomial transmissions in a complex outbreak

10.21203/rs.3.rs-305824/v1 ◽

2021 ◽

Author(s):

Laura Pérez-Lago ◽

Helena Martinez Lozano ◽

Jose Antonio pajares Diaz ◽

Arantxa Diaz Gomez ◽

Marina Machado ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Healthcare Workers ◽

Virulent Strain ◽

Control Measures ◽

Protective Equipment ◽

Whole Genome ◽

Single Patient ◽

High Fatality Rate ◽

Depth Analysis

Abstract SARS-CoV-2 nosocomial outbreaks in the first COVID-19 wave were likely associated to a shortage of personal protective equipment and scare indications on control measures. Having covered these limitations, updates on current SARS-CoV-2 nosocomial outbreaks are required. We carried out an in-depth analysis of a 27-day nosocomial outbreak in a gastroenterology ward in our hospital, potentially involving 15 patients and three healthcare workers. Patients had stayed in one of three neighbouring rooms in the ward. The severity of the infections in six of the cases and a high fatality rate suggested the possible involvement of a single virulent strain persisting in those rooms. Whole genome sequencing of the strains from 12 patients and one healthcare worker revealed an unexpected complexity. Five different SARS-CoV-2 strains were identified, two infecting a single patient each, ruling out their relationship with the outbreak; the remaining three strains were involved in three independent overlapping limited transmission clusters with three, three, and five cases. Whole genome sequencing was key to understand the complexity of this outbreak.

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Efficient whole genome sequencing of influenza A viruses

10.1101/749234 ◽

2019 ◽

Author(s):

Marina Escalera-Zamudio ◽

Ana Georgina Cobián-Güemes ◽

Blanca Taboada ◽

Irma López-Martínez ◽

Joel Armando Vázquez-Pérez ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Influenza A Virus ◽

Genome Sequencing ◽

Influenza A ◽

Genetic Material ◽

Influenza Viruses ◽

Epidemiological Surveillance ◽

Clinical Samples ◽

Whole Genome ◽

Influenza A Viruses

ABSTRACTThe constant threat of emergence for novel pathogenic influenza A viruses with pandemic potential, makes full-genome characterization of circulating influenza viral strains a high priority, allowing detection of novel and re-assorting variants. Sequencing the full-length genome of influenza A virus traditionally required multiple amplification rounds, followed by the subsequent sequencing of individual PCR products. The introduction of high-throughput sequencing technologies has made whole genome sequencing easier and faster. We present a simple protocol to obtain whole genome sequences of hypothetically any influenza A virus, even with low quantities of starting genetic material. The complete genomes of influenza A viruses of different subtypes and from distinct sources (clinical samples of pdmH1N1, tissue culture-adapted H3N2 viruses, or avian influenza viruses from cloacal swabs) were amplified with a single multisegment reverse transcription-PCR reaction and sequenced using Illumina sequencing platform. Samples with low quantity of genetic material after initial PCR amplification were re-amplified by an additional PCR using random primers. Whole genome sequencing was successful for 66% of the samples, whilst the most relevant genome segments for epidemiological surveillance (corresponding to the hemagglutinin and neuraminidase) were sequenced with at least 93% coverage (and a minimum 10x) for 98% of the samples. Low coverage for some samples is likely due to an initial low viral RNA concentration in the original sample. The proposed methodology is especially suitable for sequencing a large number of samples, when genetic data is urgently required for strains characterization, and may also be useful for variant analysis.

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From partial to whole genome imputation of SARS-CoV-2 for epidemiological surveillance

10.1101/2021.04.13.439668 ◽

2021 ◽

Author(s):

Francisco M Ortuno ◽

Carlos Loucera ◽

Carlos S Casimiro-Soriguer ◽

Jose A Lepe ◽

Pedro Camacho Martinez ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

High Rate ◽

Epidemiological Surveillance ◽

Primary Data ◽

Whole Genome ◽

Sequencing Data ◽

Wide Range ◽

Commercial Kits ◽

Almost All

The current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data. We developed impuSARS, an application that includes Minimac, the most widely used strategy for genomic data imputation and, taking advantage of the enormous amount of SARS-CoV-2 whole genome sequences available, a reference panel containing 239,301 sequences was built. The impuSARS application was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing) showing great fidelity when reconstructing the original sequences. The impuSARS application is also able to impute whole genomes from commercial kits covering less than 20% of the genome or only from the Spike protein with a precision of 0.96. It also recovers the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (< 20%). Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. impuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole genome sequencing.

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